code: def forward(self, x):
      out = self.conv1(x)
      out = self.bn1(out)
      out = self.activation(out)
      out = self.conv2(out)
      out = self.bn2(out)
      x1 = self.activation(out)  # N x 32 x 256 x 256
      out = self.conv3(x1)
      out = self.bn3(out)
      out = self.activation(out)
  
      x2 = self.layer1(out)  # N x 64 x 128 x 128
      x3 = self.layer2(x2)  # N x 128 x 64 x 64
      x4 = self.layer3(x3)  # N x 256 x 32 x 32
      out = self.layer_bottleneck(x4)  # N x 512 x 16 x 16
  
      fea1 = self.shortcut[0](x)  # input image and trimap
      fea2 = self.shortcut[1](x1)
      fea3 = self.shortcut[2](x2)
      fea4 = self.shortcut[3](x3)
      fea5 = self.shortcut[4](x4)
  
      return out, {
          "shortcut": (fea1, fea2, fea3, fea4, fea5),
          "image": x[:, :3, ...],
      }
  
imports: import paddle
  import paddle.nn
  import paddle.nn.functional
  from paddleseg.cvlibs import manager, param_init
  from paddleseg.utils import utils
  from ppmatting.models.layers import GuidedCxtAtten
label_desc: Use image node_id 3 for calling the ResShortCut_D obj's underlying member method code with example usage: obj.forward(x) and returns: out,  dict